Plant phenotypes are described using a variety of formats, but primarily using free text. While this enables some limited comparison of phenotype data across a single species, or within a knowledge domain such as leaf development or maize breeding, queries that span a broader set of species are not possible in the absence of a common template for describing phenotypes. A pilot project has been undertaken to formalize phenotype descriptors for six plant species, encompassing both crops and model species, and focusing on mutant phenotypes associated with known, sequenced genes. Mutant phenotypes of Arabidopsis, maize, rice, soybean, tomato, and Medicago were manually curated and the free text descriptions were converted into a common Entity-Quality format using taxonomically broad ontologies (Plant Ontology, Gene Ontology, ChEBI, PATO and EO). Cross-species and cross-domain phenotype comparisons and semantic similarity analyses are enabled by utilizing standardized ontology terms and associated relations. The ontology-based phenotypic descriptions are being compared to an existing classification of plant phenotypes. In addition, the semantic similarity dataset is being evaluated for its ability to enhance predictions of gene families, gene functions, and shared metabolic pathways across the six species. The use of ontologies, annotation standards, formats and best practices for plant phenotype data is a novel approach which can be expanded to other plant species, with less well-characterized genomes. These tools will enable us to explore the relationship between gene function, sequence similarity, and phenotypic similarity to make predictions useful for crop improvement.